The present invention, in some embodiments thereof, relates to neurophysiology and, more particularly, but not exclusively, to method and system for estimating the likelihood of brain concussion.
Mild traumatic brain injury (mTBI), commonly known as brain concussion, or simply “concussion,” describes an insult to the head that, in turn, causes an injury to the brain. It most often occurs from direct contact to the head but can also result from indirect injury (e.g., whiplash injury or violent shaking of the head).
The brain is a soft, jell-like structure covered with a dense network of blood vessels and contains billions of nerve cells and a complexity of interconnecting fibers. The brain is a well-protected part of the body enclosed in the skull and cushioned in the cerebrospinal fluid. A head trauma, such as a direct impact to the head or rapid movement thereof, can cause the brain to rebound against the skull, potentially causing a tearing and twisting of the structures and blood vessels of the brain resulting in a disturbance of function of the electrical activity of the nerve cells in the brain and a breakdown of the usual flow of messages within the brain. A head trauma can cause multiple shearing injuries which stretch and tear the soft nerve tissue and cause multiple points of bleeding from small blood vessels of the brain.
Individuals who have suffered one brain injury are more at risk for a second brain injury and more susceptible for subsequent injuries. Regardless of the severity, the second injury to the brain can be life-threatening if incurred within a short time interval. Additional risks from a series of concussions include premature senility and Alzheimer's disease.
There is a concern in various contact sports, such as football, hockey and soccer, of brain concussion due to impact to the head. During such physical activity, the head or other body part of the individual is often subjected to direct contact to the head which results in impact to the skull and brain of the individual as well as movement of the head or body part itself. Much remains unknown about the response of the brain to head accelerations in the linear and rotational directions and even less about the correspondence between specific impact forces and injury, particularly with respect to injuries caused by repeated exposure to impact forces of a lower level than those that result in a catastrophic injury or fatality.
Neurophysiological activity is altered following traumatic brain injury resulting, in the initial phases of post-injury, in neuronal hyperexcitability. Electrophysiological analysis of patients with cerebral trauma and concussion was first reported in the 1970's. It was proposed that the analysis of the coherence of post traumatic EEG waves may detect and quantify diffuse axonal injury.
Known in the art are methods for identifying brain injury.
U.S. Pat. No. 7,720,530 discloses a method for providing an on-site diagnosis of a subject to determine the presence and severity of a concussion. EEG signals are acquired from the subject. The signals are processed using a non-linear signal processing algorithm which denoises the detected signals, extracts features from the denoised signals, builds discriminant functions for classifying the extracted features, and detects the presence and severity of a concussion based on the classified features.
U.S. Published Application No. 20100022907 teaches that phase synchronization in an EEG signal is indicative of a site of brain injury.
Also known are general techniques that identify discrete participating regions for the purpose of relating behavioral functions to their underlying localized brain activities, or perform flow analysis.
U.S. Pat. No. 6,792,304 discloses a method and a system for mass communication assessment. A cognitive task is transmitted from a central control site to a plurality of remote test sites via Internet. The brain response of the subjects at the remote sites in response to the task is recorded and transmitted back to the central control site via the Internet. The central control site then computes the variations in the brain activities for the subjects at each of the selected sites.
U.S. Published Application No. 20040059241 discloses a method for classifying and treating physiologic brain imbalances. Neurophysiologic techniques are used for obtaining a set of analytic brain signals from a subject, and a set of digital parameters is determined from the signals. The digital parameters are quantitatively mapped to various therapy responsivity profiles. The signals and parameters for a subject are compared to aggregate neurophysiologic information contained in databases relating to asymptomatic and symptomatic reference populations, and the comparison is used for making treatment recommendations. Treatment response patterns are correlated as a dependent variable to provide a connection to successful outcomes for clinical treatment to of afflicted subjects.
International Publication No. WO 2007/138579, the contents of which are hereby incorporated by reference, describes a method for establishing a knowledge base of neuropsychological flow patterns. Signals from multiple research groups for a particular behavioral process are obtained, and sources of activity participating in the particular behavioral functions are localized. Thereafter, sets of patterns of brain activity are identified, and neuropsychological analysis is employed for analyzing the localized sources and the identified patterns. The analysis includes identification and ranking of possible pathways. A set of flow patterns is then created and used as a knowledge base. The knowledge base is then used as a constraint for reducing the number of ranked pathways.
International Publication Nos. WO 2009/069134, WO 2009/069135 and WO 2009/069136, the contents of which are hereby incorporated by reference, describe a technique in which neurophysiological data are collected before and after the subject has performed a task and/or action that forms a stimulus. The stimulus is used for defining features in the data, and the data are decomposed according to the defined features. Thereafter, the features are analyzed to determine one or more patterns in the data. The decomposition can employ clustering for locating one or more important features in the data, wherein a collection of clusters forms an activity network. The data patterns can be analyzed for defining a neural model which can be used for simulating the effect of a particular pathology and/or treatment on the brain.
Additional background art includes U.S. Published Application No. 20050177058, which discloses a system in which EEG readings from more than one subject at the same or different locations are collected, analyzed and compared, when they are exposed to a common set of stimuli. The compatibility of the subjects is studied using their EEG readings, and concealed information is discovered or verified from.